IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i19p8626-d1758224.html

Unveiling the Dynamic Interplay of Industrial Carbon Emissions: Insights from Quantile Time–Frequency Analysis

Author

Listed:
  • Wei Jiang

    (School of Economics, Qingdao University, Qingdao 266100, China)

  • Xiaoliang Guo

    (School of Economics, Qingdao University, Qingdao 266100, China)

  • Xin Li

    (School of Economics, Qingdao University, Qingdao 266100, China)

  • Xuantao Wang

    (School of Business Administration, Guangdong University of Finance, Guangzhou 510521, China)

  • Dianguang Liu

    (School of Business, Qingdao University, Qingdao 266100, China)

Abstract

Reducing carbon emissions in the industrial sector is a critical component of achieving green and sustainable development. We employ quantile vector autoregressive methods to analyze the dynamic interactions of industrial carbon emissions across various countries. Initially, we observe that, under normal conditions, developed countries led by the EU exhibit a significant total spillover effect. Secondly, during extreme quantile conditions, the spillover effects of EU-led developed countries shift from positive to negative, whereas in the UK, the opposite trend is observed. This highlights the importance of considering carbon transfer’s role in emission reduction during extreme quantile scenarios. Thirdly, we find that China’s industrial carbon emissions spillover effects remain relatively stable at all times. Lastly, total spillover effects are highly volatile during extreme market conditions, such as the COVID-19 pandemic. These findings will help clarify each country’s emission reduction responsibilities within the international industrial system and facilitate a more equitable allocation of emission reduction tasks.

Suggested Citation

  • Wei Jiang & Xiaoliang Guo & Xin Li & Xuantao Wang & Dianguang Liu, 2025. "Unveiling the Dynamic Interplay of Industrial Carbon Emissions: Insights from Quantile Time–Frequency Analysis," Sustainability, MDPI, vol. 17(19), pages 1-21, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:19:p:8626-:d:1758224
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/19/8626/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/19/8626/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhiyong Yang & Wenjie Dong & Jinfeng Xiu & Rufeng Dai & Jieming Chou, 2015. "Structural Path Analysis of Fossil Fuel Based CO2 Emissions: A Case Study for China," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-25, September.
    2. Adekoya, Oluwasegun B. & Asl, Mahdi Ghaemi & Oliyide, Johnson A. & Izadi, Parviz, 2023. "Multifractality and cross-correlation between the crude oil and the European and non-European stock markets during the Russia-Ukraine war," Resources Policy, Elsevier, vol. 80(C).
    3. Adeleke, Musefiu A. & Awodumi, Olabanji B. & Adewuyi, Adeolu O., 2022. "Return and volatility connectedness among commodity markets during major crises periods: Static and dynamic analyses with asymmetries," Resources Policy, Elsevier, vol. 79(C).
    4. Zengkai Zhang & Dabo Guan & Ran Wang & Jing Meng & Heran Zheng & Kunfu Zhu & Huibin Du, 2020. "Embodied carbon emissions in the supply chains of multinational enterprises," Nature Climate Change, Nature, vol. 10(12), pages 1096-1101, December.
    5. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    6. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    7. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    8. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    9. Yan, Yunfeng & Wang, Ran & Zheng, Xiuxiu & Zhao, Zhongxiu, 2020. "Carbon endowment and trade-embodied carbon emissions in global value chains: Evidence from China," Applied Energy, Elsevier, vol. 277(C).
    10. Kilian, Lutz & Zhou, Xiaoqing, 2022. "Oil prices, exchange rates and interest rates," Journal of International Money and Finance, Elsevier, vol. 126(C).
    11. Jiang, Wei & Chen, Yunfei, 2022. "The time-frequency connectedness among carbon, traditional/new energy and material markets of China in pre- and post-COVID-19 outbreak periods," Energy, Elsevier, vol. 246(C).
    12. Xuemei Jiang & Quanrun Chen & Dabo Guan & Kunfu Zhu & Cuihong Yang, 2016. "Revisiting the Global Net Carbon Dioxide Emission Transfers by International Trade: The Impact of Trade Heterogeneity of China," Journal of Industrial Ecology, Yale University, vol. 20(3), pages 506-514, June.
    13. Meng, Bo & Peters, Glen P. & Wang, Zhi & Li, Meng, 2018. "Tracing CO2 emissions in global value chains," Energy Economics, Elsevier, vol. 73(C), pages 24-42.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Al-Nassar, Nassar S. & Assaf, Rima & Chaibi, Anis & Makram, Beljid, 2024. "The nexus between mineral, renewable commodities, and regional stock sectors during health and military crises," Resources Policy, Elsevier, vol. 96(C).
    2. Aysan, Ahmet Faruk & Batten, Jonathan & Gozgor, Giray & Khalfaoui, Rabeh & Nanaeva, Zhamal, 2024. "Metaverse and financial markets: A quantile-time-frequency connectedness analysis," Research in International Business and Finance, Elsevier, vol. 72(PB).
    3. Le, Trung H. & Pham, Linh & Do, Hung X., 2023. "Price risk transmissions in the water-energy-food nexus: Impacts of climate risks and portfolio implications," Energy Economics, Elsevier, vol. 124(C).
    4. Andrea Bastianin & Chiara Casoli & Evzen Kocenda & Xiao Li, 2026. "Extreme Connectedness among Energy Transition Metals and Commodity Markets," Working Papers 2026.13, Fondazione Eni Enrico Mattei.
    5. Motegi, Kaiji & Sugano, Saki, 2025. "Cross-regional spillover effects of sustainability indices: A heteroscedasticity-robust VAR approach," International Review of Financial Analysis, Elsevier, vol. 108(PA).
    6. Wang, Wei & Enilov, Martin & Stankov, Petar, 2025. "Can cryptocurrency or gold rescue BRICS stocks amid the Russia-Ukraine conflict?," International Review of Financial Analysis, Elsevier, vol. 104(PA).
    7. Umar, Zaghum & Bossman, Ahmed, 2023. "Quantile connectedness between oil price shocks and exchange rates," Resources Policy, Elsevier, vol. 83(C).
    8. Yang Liu & Tongshuai Qiao & Liyan Han, 2022. "Does clean energy matter? Revisiting the spillovers between energy and foreign exchange markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2068-2083, November.
    9. Yousaf, Imran & Abrar, Afsheen & Ali, Shoaib & Goodell, John W., 2024. "Connectedness between energy cryptocurrencies and US equity markets: A quantile-based analysis," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    10. Alomari, Mohammed & Belghouthi, Houssem Eddine & Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2024. "Extreme time-frequency connectedness between energy sector markets and financial markets," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 847-877.
    11. Cevik, Emrah Ismail & Caliskan Terzioglu, Hande & Kilic, Yunus & Bugan, Mehmet Fatih & Dibooglu, Sel, 2024. "Interconnectedness and systemic risk: Evidence from global stock markets," Research in International Business and Finance, Elsevier, vol. 69(C).
    12. Su, Xianfang & Zhao, Yachao, 2023. "What has the strongest connectedness with clean energy? Technology, substitutes, or raw materials," Energy Economics, Elsevier, vol. 128(C).
    13. Ghaemi Asl, Mahdi & Nie, Pu-yan & Charkh, Cyrus, 2024. "Cycles-specific benefits of smart transport for sustainable investing: Global and regional perspectives with different ethical paradigms," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    14. Koulmas, Pavlos & Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Karadimitropoulou, Aikaterini & Karkalakos, Sotiris, 2024. "Energy firms in China towards resilience: A dynamic quantile connectedness approach," Energy Economics, Elsevier, vol. 139(C).
    15. Al-Fayoumi, Nedal & Bouri, Elie & Abuzayed, Bana, 2023. "Decomposed oil price shocks and GCC stock market sector returns and volatility," Energy Economics, Elsevier, vol. 126(C).
    16. Wang, Jue & Zhou, Yuqin & Wu, Shan, 2025. "Quantile time-frequency connectedness and portfolio diversification: A study of clean energy and metal markets," Renewable Energy, Elsevier, vol. 238(C).
    17. Mbarek, Marouene & Msolli, Badreddine, 2025. "Assessing linkages between supply chain tokens and other assets: Evidence from a time-frequency quantile connectedness approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 46(C).
    18. Jareño, Francisco & Yousaf, Imran, 2023. "Artificial intelligence-based tokens: Fresh evidence of connectedness with artificial intelligence-based equities," International Review of Financial Analysis, Elsevier, vol. 89(C).
    19. Su, Chi-Wei & Pang, Li-Dong & Qin, Meng & Lobonţ, Oana-Ramona & Umar, Muhammad, 2023. "The spillover effects among fossil fuel, renewables and carbon markets: Evidence under the dual dilemma of climate change and energy crises," Energy, Elsevier, vol. 274(C).
    20. Izunna Anyikwa & Andrew Phiri, 2023. "Connectedness and spillover between African equity, commodity, foreign exchange and cryptocurrency markets during the COVID-19 and Russia-Ukraine conflict," Future Business Journal, Springer, vol. 9(1), pages 1-18, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:19:p:8626-:d:1758224. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.